KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples

Minich, Jeremiah J.; Zhu, Quanyin; Janssen, Stefan; Hendrickson, Ryan C.; Almasi‐Hashiani, Amir; Vetter, Russ; Hyde, John R.; Doty, Megan M.; Stillwell, Kristina; Benardini, James N.; Kim, Jae; Allen, Eric E.; Venkateswaran, Kasthuri; Knight, Rob

doi:10.1128/msystems.00218-17

Cited by 125 publications

(174 citation statements)

References 37 publications

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“…The use of Illumina shotgun metagenomics by Brooks et al was key to characterizing strain polymorphisms and relatedness of pathogens in low diversity neonatal ICU environments 26 . Several limitations remain for the use of shotgun metagenomics in general, including low microbial biomass, the presence of nosocomial strains at low relative abundances, the presence of multiple strains, computational constraints in strain-level analysis 27 , and the shortcomings of short-read metagenomics for assembling high-contiguity, strainresolved genomes for detailed genetic analysis 24,26,28,29 .…”

Section: Introductionmentioning

confidence: 99%

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Chng

Bertrand

et al. 2019

Preprint

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There is growing attention surrounding hospital acquired infections (HAIs) due to high associated healthcare costs, compounded by the scourge of widespread multi-antibiotic resistance. Although hospital environment disinfection is well acknowledged to be key for infection control, an understanding of colonization patterns and resistome profiles of environment-dwelling microbes is currently lacking. We report the first extensive genomic characterization of microbiomes (355), common HAI-associated microbes (891) and transmissible drug resistance cassettes (1435) in a tertiary hospital environment based on a 2-timepoint sampling of 179 sites from 45 beds. Deep shotgun metagenomic sequencing unveiled two distinct ecological niches of microbes and antibiotic resistance genes characterized by biofilm-forming and human microbiome influenced environments that display corresponding patterns of divergence over space and time. To study common nosocomial pathogens that were typically present at low abundances, a combination of culture enrichment and long-read nanopore sequencing was used to obtain thousands of high contiguity genomes (2347) and closed plasmids (5910), a significant fraction of which (>58%) are not represented in current sequence databases. These high-quality assemblies and metadata enabled a rich characterization of resistance gene combinations, plasmid architectures, and the dynamic nature of hospital environment resistomes and their reservoirs. Phylogenetic analysis identified multidrug resistant clonal strains as being more widely disseminated and stably colonizing across hospital sites. Further genomic comparisons with clinical isolates across multiple species supports the hypothesis that multidrug resistant strains can persist in the hospital environment for extended periods (>8 years) to opportunistically infect patients. These findings highlight the importance of characterizing antibiotic resistance reservoirs in the hospital environment and establishes the feasibility of systematic genomic surveys to help target resources more efficiently for preventing HAIs.

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Section: Introductionmentioning

confidence: 99%

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Chng

Bertrand

et al. 2019

Preprint

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“…Using fewer PCR steps, we decrease error rates and chimera formation, as previously reported 18,21 . The agarose gel check after library amplifications can still be useful for samples with sufficient biomass, though it is often the case that low biomass samples show no visible bands, hampering any useful interpretation 12 . For this reason, we do not check for amplicons in agarose gels.…”

Section: Equivolumetric Protocol For Amplicon Library Preparationmentioning

confidence: 99%

“…In our protocol, PCR pooling is also performed in an equivolumetric fashion, and DNA sequencing follows as in traditional methods. The main justification for our proposal is the fact that samples from indoor environments vary widely in terms of total biomass, generally characterizing low biomass samples [12][13][14][15] and thus rendering relative information less useful.…”

Section: Equivolumetric Protocol For Amplicon Library Preparationmentioning

confidence: 99%

“…Faecal samples are generally characterized by high biomass, while hospital and indoor samples usually present low biomass 13,15,22 . Low biomass samples impose more challenges to their processing because of contamination and process inefficiencies 12 . In fact, in this study we removed E. coli sequences from our results since these were frequently detected in our negative controls.…”

Section: Equivolumetric Protocol Input Dna and Absolute Bacterial Amentioning

confidence: 99%

“…is an arbitrary sum, without biological relevance, yielding microbiome data as necessarily compositional in nature 8,10,11 . Nonetheless, a previous study has demonstrated that library sizes need not be arbitrary, potentially holding significant correlations with input bacterial cell counts 12 .…”

Section: Introductionmentioning

confidence: 99%

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Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing

Gnf¹,

Ap²,

Lfv³

2020

Preprint

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Next-generation sequencing (NGS) has been extensively employed to perform microbiome characterization worldwide. As a culture-independent methodology, it has allowed high-level profiling of sample microbial composition. However, most studies are limited to information regarding relative bacterial abundances, ignoring scenarios in which sample microbe biomass can vary widely. Here, we develop an equivolumetric protocol for amplicon library preparation capable of generating NGS data responsive to input DNA, recovering proportionality between observed read counts and absolute bacterial abundances. Under specified conditions, we argue that the estimation of colony-forming units (CFU), the most common unit of bacterial abundance in classical microbiology, is challenged mostly by resolution and taxon-to-taxon variation. We propose Bayesian cumulative probability models to address such issues. Our results indicate that predictive errors vary consistently below one order of magnitude for observed bacteria. We also demonstrate our approach has the potential to generalize to previously unseen bacteria, but predictive performance is hampered by specific taxa of uncommon profile. Finally, it remains clear that NGS data are not inherently restricted to relative information only, and microbiome science can indeed meet the working scales of traditional microbiology.

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Gut Microbiome in Patients With Early-Stage and Late-Stage Melanoma

Witt,

Cass,

Tran

et al. 2023

JAMA Dermatol

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ImportanceThe gut microbiome modulates the immune system and responses to immunotherapy in patients with late-stage melanoma. It is unknown whether fecal microbiota profiles differ between healthy individuals and patients with melanoma or if microbiota profiles differ among patients with different stages of melanoma. Defining gut microbiota profiles in individuals without melanoma and those with early-stage and late-stage melanoma may reveal features associated with disease progression.ObjectiveTo characterize and compare gut microbiota profiles between healthy volunteers and patients with melanoma and between patients with early-stage and late-stage melanoma.Design, Setting, and ParticipantsThis single-site case-control study took place at an academic comprehensive cancer center. Fecal samples were collected from systemic treatment−naive patients with stage I to IV melanoma from June 1, 2015, to January 31, 2019, and from healthy volunteers from June 1, 2021, to January 31, 2022. Patients were followed up for disease recurrence until November 30, 2021.Main Outcomes and MeasuresFecal microbiota was profiled by 16S ribosomal RNA sequencing. Clinical and pathologic characteristics, treatment, and disease recurrence were extracted from electronic medical records. Fecal microbiome diversity, taxonomic profiles and inferred functional profiles were compared between groups.ResultsA total of 228 participants were enrolled (126 men [55.3%]; median age, 59 [range, 21-90] years), including 49 volunteers without melanoma, 38 patients with early-stage melanoma (29 with stage I or melanoma in situ and 9 with stage II), and 141 with late-stage melanoma (66 with stage III and 75 with stage IV). Community differences were observed between patients with melanoma and volunteers. Patients with melanoma had a higher relative abundance of Fusobacterium compared with controls on univariate analysis (0.19% vs 0.003%; P &lt; .001), but this association was attenuated when adjusted for covariates (log2 fold change of 5.18 vs controls; P = .09). Microbiomes were distinct between patients with early-stage and late-stage melanoma. Early-stage melanoma had a higher alpha diversity (Inverse Simpson Index 14.6 [IQR, 9.8-23.0] vs 10.8 [IQR, 7.2-16.8]; P = .003), and a higher abundance of the genus Roseburia on univariate analysis (2.4% vs 1.2%; P &lt; .001) though statistical significance was lost with covariate adjustment (log2 fold change of 0.86 vs controls; P = .13). Multiple functional pathways were differentially enriched between groups. No associations were observed between the microbial taxa and disease recurrence in patients with stage III melanoma treated with adjuvant immunotherapy.Conclusions and RelevanceThe findings of this case-control study suggest that fecal microbiota profiles were significantly different among patients with melanoma and controls and between patients with early-stage and late-stage melanoma. Prospective investigations of the gut microbiome and changes that occur with disease progression may identify future microbial targets for intervention.

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KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples

Cited by 125 publications

References 37 publications

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Cartography of opportunistic pathogens and antibiotic resistance genes in a tertiary hospital environment

Equivolumetric protocol generates library sizes proportional to total microbial load in next-generation sequencing

Gut Microbiome in Patients With Early-Stage and Late-Stage Melanoma

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